You can train a traditional classifier on it quite well.
But the one-shot and few-shot classification performance of decision models really needs in-context learning. The most common way of getting that is by grafting a small LLM onto it, which is certainly possible.
At that point though, why not just use a small LLM with audio capabilities. Gemma E2B is a good model that is already setup for this, and training a decision model LoRA adapter is very easy.
But the one-shot and few-shot classification performance of decision models really needs in-context learning. The most common way of getting that is by grafting a small LLM onto it, which is certainly possible.
At that point though, why not just use a small LLM with audio capabilities. Gemma E2B is a good model that is already setup for this, and training a decision model LoRA adapter is very easy.
Edit: Apparently people have got decision models working on EmbeddingGemma, eg: https://huggingface.co/mrm8488/embeddinggemma-2-ft-typed-dec.... I'm not seeing it ranked on https://huggingface.co/spaces/multimodalart/jev-decision-ind... so I have questions about how well it does in-context learning.